Ovarian cancer (OC) often goes undetected until advanced stages due to mild early symptoms. This research proposes a novel methodology for assessing OC severity through histopathological image analysis, utilizing Rank-Based Leaf in Wind Optimization and Alpha Piecewise Linear Fuzzy techniques. It enhances tissue image quality through normalization and Contrast Limited Adaptive Histogram Equalization, employs ResNet 50 with Inception v4 for feature extraction, and uses a ranking layer to prioritize key features. The model achieved 99.25% accuracy and 97.98% precision, effectively classifying tumor severity levels under diagnostic uncertainty. This robust approach enhances diagnostic accuracy, supports early detection, and improves treatment planning. Future work will explore cross-validation, model pruning, and real-time integration for clinical applications.

β-glucans are structurally diverse polysaccharides from fungi, yeasts, bacteria, and cereals, exhibiting variable branching and molecular weights that shape their biological activity. Emerging preclinical and clinical evidence highlights their ability to modulate innate and adaptive immunity, exerting direct and adjunct antitumor effects via dectin-1, toll-like receptors, and complement receptor 3. Although well known as nutraceuticals, their integration into advanced cancer biotherapeutics, such as monoclonal antibody regimens, cytokine modulation, and nanoparticle delivery, remains in early translation. This review examines the molecular basis of β-glucan-induced immunostimulation, emphasizing how linkage type, branching frequency, triple-helical structure, and source influence receptor engagement and downstream immune responses. Emerging evidence is presented on β-glucan formulation engineering, including β-glucan-coated polymeric nanoparticles and micelles, β-glucan-complexed lipid nanoparticles for nucleic acid delivery, polymersomes with splenic/myeloid avidity, and β-glucan-stabilized nanosuspensions, several of which show enhanced lymphatic targeting, improved drug bioavailability, or reduced tumor growth in preclinical cancer models. Clinical translation is analyzed with attention to dosing protocols, administration routes (oral, intravenous, topical), and the impact of β-glucan adjuvancy in therapeutic antibodies, immunotoxins, and vascular disrupting agents. The review further addresses essential safety and toxicology data, regulatory compliance challenges, and the imperative for rigorous physicochemical standardization to ensure clinical reproducibility and patient safety. β-glucans have emerged as multifunctional immunomodulators and drug delivery enhancers, driving progress toward personalized cancer immunotherapy and innovative combinatorial regimens. Continued interdisciplinary research and harmonization of extraction, characterization, and delivery protocols are paramount for success in precision oncology.

Liver hepatocellular carcinoma (LIHC) is a very aggressive kind of cancer that has a dramatic impact on the quality of life and mean survival of the patient. Consequently, a specific requirement emerges to predict the prognosis of individual patients as well as to guide the individualized therapeutic strategy in clinic. Telomere- related genes (TRGs) have recently been unraveled as key players in tumor biology and a constituent of the tumor immune microenvironment. Thus, the authors constructed a risk prediction model rooted in TRGs for the purpose of improving the predictive value of prognosis in LIHC patients. The data in different datasets such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus were collected in TCGA-LIHC as well as GSE116174 and GSE14520. The differential expression analysis was performed to identify telomere location-related differential expression genes (TRGs), and the gene ontology (GO) and KEGG enrichment analyses were performed to investigate the function of TRGs in bioprocess, metabolism, and signaling pathways. Prognostic risk prediction model correlated with outcome was constructed by the LASSO Cox regression model and the key genes associated with the prognosis of LIHC. The predictive capacity of the risk signature based on TRG was further confirmed in two external cohorts. The predictive ability of risk model was assessed, and a series of clinical factors associated with the prognosis of liver cancer were determined. Univariate and multivariate analyses were used to identify independent prognostic factors of LIHC. The authors discovered a set of TRG-associated DGEs with telomere states compared between LIHC and normal. Functional enrichment analysis of these DGEs indicated that they might participate in fundamental biological processes, such as genome maintenance and replication as well as multiple metabolic and signaling pathways. A risk prediction model and signature genes associated with patient prognosis were established by the LASSO Cox regression analysis for LIHC. The prognostic accuracy of the TRG-based risk model was also verified in two independent datasets. Furthermore, the prediction accuracy of the model was analyzed, and clinical indicators associated with the prognosis of liver cancer patients were enumerated. Univariate and multivariate analyses were conducted to investigate the association of clinical variables and prognosis in patients with LIHC. In conclusion, the authors validate that diagnostic, therapeutic, and prognostic accuracy would be enhanced through the study of gene expression data, construction of risk prediction models, and identification of risk-associated clinical factors of LIHC patients. The findings provide new biomarkers and risk prediction models for clinicians to better estimate the risk of patients for the purpose of treatment decisions.

Nectin-4 has been successfully used as a target for tumor therapy. Although several bicyclic peptides and antibodies, Nectin-4 positron emission tomography (PET) probes, have been reported for tumor imaging and expression detection, their production costs or pharmacokinetics still need further improvement. This study developed a novel linear peptide PET probe for rapid examination of Nectin-4-related tumors. [Ga]Ga-NOTA-SP was prepared by a one-step chelation reaction, and its quality control was carried out by using radio-high-performance liquid chromatography and thin-layer chromatography. Molecular docking was used to predict the predominant binding of NOTA-SP to Nectin-4. Cell experiments using SW780 cells and PET/computed tomography (CT) imaging, using the SW780 tumor model, were performed to assess the specific binding and targeting ability of [Ga]Ga-NOTA-SP to Nectin-4. Normal BALB/c mice were used to investigate the plasma concentration-time curves. Under optimal labeling conditions, the labeling efficiency of [Ga]Ga-NOTA-SP can reach above 95%, with a molar-specific activity of 2.45 MBq/nmol and high stability. The high specificity of [Ga]Ga-NOTA-SP to Nectin-4 is demonstrated by molecular docking and cell uptake experiment, showing a binding energy of -5.4 kcal/mol and K value of 2.483 nM, which was further confirmed by PET-CT imaging. [Ga]Ga-NOTA-SP using a linear peptide as a vector shows favorable pharmacokinetics and specific targeting ability to Nectin-4, enabling rapid tumor mouse model imaging. It would be a promising PET/CT imaging probe for optimizing Nectin-4-related tumor diagnoses and therapy.

This review assesses the promise of nanoparticles containing melatonin and lactoferrin (ML-Lf-NPs) in treating cancer, concentrating on their capacity to improve drug delivery, pinpoint tumors, and optimize therapeutic efficacy. A thorough examination of recent progress in nanoparticle-oriented drug delivery systems was performed, highlighting the physicochemical characteristics, mechanisms of action, and biological interactions of ML-Lf-NPs. Melatonin nanoparticles demonstrate antioxidant and anti-inflammatory characteristics that enhance tumor targeting and therapeutic results. Lactoferrin nanoparticles show potential anticancer effects by improving cellular absorption and enabling targeted drug release at tumors. Both systems demonstrate considerable promise for enhancing drug bioavailability and minimizing side effects. ML-Lf-NPs signify creative strategies for cancer treatment. Their distinct characteristics allow for precise delivery and improved therapeutic effectiveness, opening doors for future clinical uses in cancer treatment. [Figure: see text].

Colorectal cancer (CRC) is a leading cause of cancer mortality globally. The molecular mechanisms of CRC and the accumulating immune cell infiltration in the tumor microenvironment (TME) are essential for enhancing the treatment strategy and evaluation of the prognosis. In this study, the authors applied machine learning techniques to single-cell RNA sequencing data to investigate the gene expression characteristics of immune cells in CRC and their association with immune cell infiltration. Differentially expressed genes (DEGs) in CRC were identified by machine learning methods, including clustering analysis, survival analysis, and gene enrichment analysis, and prognostic models were constructed. CIBERSORT and ESTIMATE algorithms were used to evaluate the abundance of infiltrating immune cells and UMAP and t-SNE techniques were used for dimensionality reduction and visualization of the data. Specific gene expression patterns are closely related to immune cell infiltration in CRC patients. Clustering analysis demonstrated two unique subgroups in the CRC samples, characterized by significant differences in survival outcomes ( = 0.049). These DEGs are enriched in various biological processes, according to gene enrichment analysis. The prognostic models of the receiver operating characteristic curves had good predictive accuracy, with area under the curve values. Single-cell data analysis also showed the intricate associations of immune cells with tumor cells in the TME. This study reveals the complex relationship between gene expression and immune infiltration in CRC using machine learning techniques, and establishes prognostic models with potential value in the clinic. These findings reveal the new potential biomarkers for CRC desensitization and immunotherapy.

This study analyzed the effectiveness of proactive nursing interventions in patients undergoing ultrasound-guided radiofrequency ablation for uterine fibroids. A retrospective analysis included 50 patients who received routine postoperative care from April 2022 to April 2023 as control group (CG) and 54 patients who received proactive nursing from May 2023 to May 2024 as intervention group (IG). Eligible participants were adult women with confirmed uterine fibroids and complete medical records, including preoperative, intraoperative, and postoperative data. Exclusion criteria included individuals with severe comorbidities such as uncontrolled diabetes or hypertension, those who were pregnant or breastfeeding during the study period, and patients with significant gaps in medical records or cognitive impairments that hindered participation in the study. Surgical outcomes, ovarian function markers, immune function markers, oxidative stress indicators, and complications were compared between the two groups. In IG, intraoperative blood loss (15.83 ± 4.35 mL vs. 49.75 ± 7.62 mL), surgical duration (27.64 ± 8.04 min vs. 55.08 ± 6.67 min), hospital stay (3.17 ± 0.65 d vs. 5.48 ± 0.83 d), and time to ambulation (1.43 ± 0.27 d vs. 2.56 ± 0.34 d) were significantly lower versus CG ( < 0.05, Cohen's d = 0.72∼0.89). Levels of luteinizing hormone, follicle-stimulating hormone, estradiol, reactive oxygen species, malondialdehyde, and advanced oxidation protein products at 1 d and 30 d postoperatively were significantly lower in IG versus CG ( < 0.05, Cohen's d = 0.6∼0.80). CD3 and CD8 levels at 1 d and 30 d postoperatively were significantly lower in IG, whereas CD4 and CD4/CD8 (2.45 ± 0.56 vs. 1.58 ± 0.44) were significantly higher versus CG ( < 0.05, Cohen's d = 0.65). The incidence of postoperative complications in IG (14.81%) was significantly inferior to that in CG (22%) ( < 0.05, Cohen's d = 0.52∼0.87). Proactive nursing interventions applied in the management of patients after ultrasound-guided radiofrequency ablation for uterine fibroids demonstrate significant clinical advantages. Specifically, they reduce intraoperative bleeding, shorten surgical and hospitalization durations, and potentially benefit ovarian and immune functions of patients.

Epithelial cell adhesion molecule (EpCAM) is overexpressed in a wide range of epithelial malignancies, and thus is a potential target for antibody-based radiotherapy. This work describes the synthesis, labeling, and biological evaluation of an alpha-emitting radioconjugate, [Ac]Ac-Macropa-PEG-HEA125, as a targeted alpha therapy candidate for EpCAM-positive tumors. The murine anti-EpCAM monoclonal antibody HEA125 was site-specifically conjugated to the chelator Macropa using a PEG-maleimide linker. The structural integrity and chelator-to-antibody (C/A) ratio of the conjugate were confirmed by SDS-PAGE and LC-MS. Radiolabeling with Ac was performed under mild conditions, and radiochemical purity was assessed using iTLC and radio-HPLC. studies included stability testing, immunoreactivity, and cytotoxicity assays using MCF-7 (EpCAM) and CHO-K1 (EpCAM) cell lines. In vivo biodistribution and therapeutic efficacy were evaluated in MCF-7 xenograft-bearing female athymic nude mice (BALB/c nu/nu). Conjugation with HEA125 resulted in a C/A ratio of 4.2 ± 0.3, and SDS-PAGE proved integrity of antibodies to be preserved. Purity of radiolabeling was >98%, and >94% stability was retained for more than 120 h both in PBS and serum. Immunoreactive fraction was 86.2 ± 2.4%, and cytotoxicity assays showed, dose-dependent MCF-7 cell killing with minimal impact on EpCAM-negative controls. In vivo, [Ac]Ac-Macropa-PEG-HEA125, exhibited significant tumor uptake (15.7 ± 2.3 %ID/g at 24 h), maintained retention (12.1 ± 1.9 %ID/g at 72 h), and minimal off-target accumulation. Therapeutic injection resulted in extensive tumor growth inhibition and long-term survival, with 60% of the mice surviving past day 30 with little overt toxicity. [Ac]Ac-Macropa-PEG-HEA125, establishes high radiochemical purity, stability, EpCAM specificity, and strong antitumor activity in preclinical models. These results warrant its advancement as a promising targeted alpha therapy candidate for EpCAM-expressing carcinomas.

Hepatocellular carcinoma (HCC) is still the largest cause of cancer-related death globally, with alcohol-related HCC (AR-HCC) being a particularly difficult subtype with poor clinical results. Noninvasive biomarkers, such as the fibrosis-4 (FIB-4) index, may provide significant prognostic information that might aid in guiding new interventional techniques, such as ultrasound-based treatments. The authors did a retrospective cohort analysis on male AR-HCC patients diagnosed between January 2008 and December 2018. Clinical data and survival outcomes were obtained from electronic medical records, with HCC diagnosed as the baseline. The major endpoint was 12-month mortality. Multivariate logistic regression and limited cubic spline analysis were used to assess the relationship between FIB-4 and mortality risk. Among 786 AR-HCC patients (mean age 57 years), 90.1% reported a history of alcohol usage for more than 10 years. The Barcelona Clinic Liver Cancer staging showed 42.8% in stage 0/A, 45.9% in stage B/C, and 11.3% in stage D. Deceased individuals had substantially higher FIB-4 levels ( < 0.05). Logistic regression demonstrated that higher FIB-4 was independently related with increased mortality, and spline analysis revealed a linear risk increase with a threshold of 5.61. Elevated FIB-4 (≥5.61) predicts worse mortality in AR-HCC, indicating its potential relevance in stratifying patients for ultrasound-based cancer therapy. The level of fibrosis may impact both therapeutic response and procedural risk. Routine incorporation of FIB-4 into clinical processes may aid precision decision-making in choosing AR-HCC patients most likely to benefit from ultrasound-guided or ultrasound-enhanced biotherapeutic. alcohol, hepatocellular carcinoma, FIB-4, multivariate logistic regression analyses, mortality.

Chemotherapy, radiation, and targeted biological treatments are examples of cancer therapies that have a significant effect on the immune system. They frequently interfere with the manufacture of immunoglobulins (Igs), which results in immunodeficiency. The processes via which these medications affect B cell activity and antibody production are examined in this review, with an emphasis on cytokine regulation, bone marrow suppression, and therapy-induced lymphopenia. Reduced Ig levels can have clinical repercussions such as increased vulnerability to infections, decreased effectiveness of vaccinations, and compromised immune monitoring. This study also looks at new and existing methods to lessen these consequences, including immunomodulatory techniques, prophylactic antibiotics, and Ig replacement treatment. Optimizing patient outcomes, striking a balance between immunological protection and oncologic efficacy, and directing future research in supportive cancer care all depend on an understanding of how humoral immunity and cancer treatment interact.

To properly target tumors during preoperative chemoradiotherapy, differentiated thyroid carcinoma (DTC) must be careful. This method increases treatment success and decreases recurrence. Ultrasound coupled with SPECT/CT may provide novel localization and dose planning possibilities. Many systems solely use anatomical or functional imaging. This may result in insufficient dosage delivery and wasted radiation exposure to healthy tissues. These issues are addressed by Dual-Modality Imaging-Guided Adaptive Chemoradiotherapy Planning (DMI-ACP). This innovative approach combines real-time ultrasound imaging with 6 Å SPECT/CT imaging for precise tumor delineation and tailored dosimetry. This system enables clinicians to adjust chemoradiotherapy regimens by seamlessly integrating functional iodine absorption data with anatomical characteristics, thereby targeting therapy to cancerous areas. The outcomes of this method for patients with DTC were promising, including better lesion targeting, reduced radiation exposure to healthy tissues, and improved chemotherapeutic dose distribution. In clinical evaluations, the DMI-ACP framework demonstrated a sensitivity of 94% and a specificity of 89% in identifying malignant lesions compared with traditional imaging techniques. Furthermore, the integration of adaptive planning resulted in a 20% improvement in tumor control probability and a 15% reduction in exposure to surrounding healthy tissue, as assessed through dosimetric analysis. 2023075 Nanjing Drum Tower Hospital Group Suqian Hospital/The Affiliated Suqian Hospital of Xuzhou Medical University.

Recent research has significantly altered the understanding of the immunogenic profile of certain processes of cancer cell death, leading to the recognition of a new subclass of apoptosis called "immunogenic apoptosis." This form of cell death, induced by specific chemotherapeutic agents, has been shown to elicit a "chemotherapy vaccine effect" , effectively stimulating an antitumor immune response. At the molecular level, "a collection of molecules" known as "damage-associated molecular patterns (DAMPs)" have been identified as key contributors to the immunogenicity of various cell death pathways. Intracellular molecules, such as heat-shock proteins, high-mobility group box 1 protein, and calreticulin, act as DAMPs when exposed or secreted in response to specific certain stressors, stimuli, and modes of cell death. These discoveries have fueled ongoing research focused on the identification of novel DAMPs, uncovering new mechanisms of their exposure or secretion and developing therapeutic agents capable of inducing immunogenic cell death (ICD). In addition, there is growing interest in addressing the current challenges and limitations within this emerging paradigm. The authors believe that this integrated strategy-combining DAMPs, ICD, and anticancer therapies-may hold the key to significantly reducing cancer-related mortality in the near future.

Ocular malignancies provide a unique therapeutic challenge because of their anatomical intricacy, limited accessibility, and vision-critical nature. Recent developments in radiopharmaceutical design have been paired with ultrasound-mediated medicine administration to create highly targeted, less invasive therapies for intraocular cancers. This research looks at the emerging topic of ultrasound-responsive radiopharmaceutical devices built specifically for ocular oncology. These methods enhance tumor selectivity, decrease off-target effects, and enable real-time imaging-guided therapy by utilizing targeted ultrasound to induce localized medication release or radiotherapeutic agent activation. Microbubble-assisted delivery, thermosensitive liposomes, and phase-transition nanodroplets carrying radionuclides have all been designed to optimize ocular pharmacokinetics and tissue penetration. Preclinical studies reveal promising results in increasing radiotherapeutic efficacy against retinoblastoma and uveal melanoma while sparing healthy ocular tissues.

Malignant brain tumors remain a major therapeutic challenge due to poor intracellular delivery of therapeutics. Radiopharmaceuticals such as Technetium-99m (^Tc) are valuable for imaging and therapy but suffer from limited tumor uptake caused by cellular and membrane barriers. Focused ultrasound (FUS) offers a noninvasive strategy to transiently enhance membrane permeability through sonoporation. Unlike prior studies largely focused on blood-brain barrier disruption, this work specifically investigates direct tumor cell sonoporation as an independent uptake mechanism. This study evaluates FUS-mediated enhancement of ^Tc radiopharmaceutical uptake in brain tumor cells and determines optimal acoustic parameters balancing efficacy and safety. Human glioblastoma (U87-MG) and astrocytoma (A172) cells were cultured and exposed to FUS at intensities of 0.3, 0.5, and 0.7 W/cm for 30-120 s. Radiopharmaceutical uptake was quantified using γ-scintillation counting. Membrane integrity was assessed by live/dead fluorescence microscopy and lactate dehydrogenase release, while cell viability was evaluated via medical training therapy (MTT) assays. U87-MG cells exhibited up to a 3.1-fold increase at 0.7 W/cm for 120 s, with a 2.3-fold enhancement at the clinically relevant 0.5 W/cm for 60 s while maintaining >92% viability. A172 cells showed similar trends with slightly lower magnitudes. Safety assays confirmed reversible membrane permeabilization at ≤0.5 W/cm. The temporal uptake kinetics aligned with established membrane pore resealing dynamics, supporting reversible sonoporation as the uptake mechanism. Importantly, while ^Tc complexes are primarily diagnostic, enhanced intracellular delivery achieved by optimized FUS may also support future theranostic strategies, including radionuclide therapy. These findings underscore the translational potential of FUS in neuro-oncology, where tumor heterogeneity necessitates parameter optimization to maximize radiopharmaceutical delivery, improve imaging contrast, and overcome therapeutic resistance.

Accurate and noninvasive breast cancer grading and therapy monitoring remain critical challenges in oncology. Traditional methods often rely on invasive histopathological assessments or imaging-only techniques, which may not fully capture the molecular and morphological intricacies of tumor response. This article presents a novel, noninvasive framework for breast cancer analysis and therapy monitoring that combines two parallel mechanisms: (1) a dual-stream convolutional neural network (CNN) processing high-intensity ultrasound images, and (2) a biomarker-aware CNN stream utilizing patient-specific breast cancer biomarkers, including carbohydrate antigen 15-3, carcinoembryonic antigen, and human epidermal growth factor receptor 2 levels. The imaging stream extracts spatial and morphological features, while the biomarker stream encodes quantitative molecular indicators, enabling a multimodal understanding of tumor characteristics. The outputs from both streams are fused to predict the cancer grade (G1-G3) with high reliability. Experimental evaluation on a cohort of pre- and postchemotherapy patients demonstrated the effectiveness of the proposed approach, achieving an overall grading accuracy of 97.8%, with an area under the curve of 0.981 for malignancy classification. The model also enables quantitative post-therapy analysis, revealing an average tumor response improvement of 41.3% across the test set, as measured by predicted regression in grade and changes in biomarker-imaging correlation. This dual-parallel artificial intelligence strategy offers a promising noninvasive alternative to traditional histopathological and imaging-alone methods, supporting real-time cancer monitoring and personalized treatment evaluation. The integration of high-resolution imaging with biomolecular data significantly enhances diagnostic depth, paving the way for intelligent, patient-specific breast cancer management.

Colorectal cancer (CRC) remains a significant factor contributing to the morbidity and mortality rates linked with cancer throughout the world, especially in its stages of progression. Increasingly attractive therapeutic options include immune modulation combined with preoperative chemotherapy and radiation therapy (CRT). Recent studies have revealed that the protein serine peptidase inhibitor Kazal type 4 (SPINK4), which is abundantly expressed in gastrointestinal tract tissues, plays a role in immune evasion and treatment resistance in cancers. This meta-analysis aims to assess the relationship between SPINK4 expression levels and the therapeutic effectiveness of radiolabeled immune modulators in patients with advanced CRC who are undergoing preoperative chemotherapy and radiation treatment. The degree of SPINK4 expression and a lower objective response to radiolabeled immune modulators showed a statistically significant link. Conversely, patients with low SPINK4 expression have more favorable treatment responses and ongoing clinical improvement following CRT. High SpINK4 expression can act as a negative prognostic biomarker for radiolabeled immune control in advanced CRC.

Response to neoadjuvant chemotherapy (NACT) in locally advanced gastric cancer varies. This study compares tumor response to NACT across anatomical locations, considering clinicopathological differences. This retrospective study included 212 patients with gastric adenocarcinoma who received NACT followed by surgery. Tumors were classified by location (antrum-pylorus, corpus-fundus, cardia). Treatment response was assessed using the Modified Ryan Scoring System (0 = complete, 1 = near complete, 2 = partial, 3 = minimal/none). Tumor locations were antrum-pylorus (30.2%), corpus-fundus (28.3%), and cardia (41.5%). Localization showed no statistically significant differences in response ( = 0.337). However, cardia tumors were more frequent in Groups 3 (40.9%) and 4 (48.1%), which showed poorer pathological responses, whereas antrum (34.6%) and corpus (38.5%) tumors were more common in Group 1, representing patients with a pathological complete response. These findings suggest that cardia tumors may have a lower response to NACT, although definitive conclusions cannot be drawn. In multivariate analysis, only advanced T stage (T3-4) was independently associated with poor tumor regression grade response (odds ratio 14.3, 95% confidence interval 5.4-37.5, < 0.001). Tumor response to NACT varied by anatomical location, although differences were not statistically significant. Cardia tumors showed a trend toward lower response rates. To the authors' knowledge, this is the first study evaluating gastric anatomical subgroups in this context. While not conclusive, the findings suggest that tumor location may influence treatment strategies, warranting validation in larger studies.

Oral squamous cell carcinoma (OSCC) is the most prevalent malignancy of the neck and head region. A major contributor to poor prognosis in OSCC is bone infiltration. Bone morphogenetic protein 2 (BMP2), known to promote tumor progression and bone metastasis in several cancers, has recently emerged as a potential molecular mediator of OSCC invasiveness. However, its role in predicting therapeutic response-particularly in emerging modalities like ultrasound-based therapies-remains unexplored. The authors assessed BMP2 expression in OSCC tissues and cell lines using RT-qPCR. Functional assays were conducted to evaluate malignant cellular behaviors, including proliferation and epithelial-mesenchymal transition (EMT). Osteoclast differentiation and bone resorption were quantified via TRAP staining and resorption pit assays. RNA-binding interactions were identified using RNA immunoprecipitation and biotin pull-down assays. BMP2 was significantly overexpressed in OSCC and strongly correlated with bone infiltration. Its upregulation enhanced OSCC cell proliferation, EMT, and osteoclast-mediated bone resorption. , BMP2 knockdown suppressed tumor growth and bone invasion. Mechanistically, the authors identified ELAVL1 as a key RNA-binding protein that stabilized BMP2 transcripts, thereby promoting its expression. Moreover, BMP2 overexpression rescued the tumor-suppressive effects of ELAVL1 silencing, highlighting a critical regulatory axis. Given the role of BMP2 in modulating the tumor microenvironment and its association with bone-invasive phenotypes, it holds potential as a predictive biomarker for response to ultrasound-enhanced therapeutic strategies. ELAVL1-regulated BMP2 promotes OSCC progression and bone infiltration and may serve as a valuable predictive biomarker for therapeutic response in ultrasound-guided biotherapies.

Immune-resistant lung carcinoma poses a major hurdle for effective cancer treatment, largely due to its dense tumor microenvironment (TME) and the challenges of drug penetration. To boost the effectiveness of radiopharmaceuticals in this intricate TME, focused ultrasound-mediated microbubble cavitation (FUS-MMC) needs to enhance their accessibility. Current delivery methods often fall short, suffering from limited vascular permeability and insufficient tumor uptake. This results in less effective treatments and increased off-target toxicity. To address this issue, this article proposes a targeted delivery framework that utilizes FUS-MMC. This innovative technique involves administering microbubbles systemically and directing ultrasound precisely to disrupt the tumor's blood vessels and extracellular matrix temporarily. By using the FUS-MMC approach, the permeability of the TME is improved, allowing radiopharmaceuticals like 177Lu-DOTATATE to penetrate deeper into the tumor tissues. This enhanced access leads to a more even distribution and greater accumulation of therapeutic agents right at the tumor site. FUS-MMC significantly boosts the efficiency of radiopharmaceutical delivery, reduces systemic exposure, and improves tumor response rates in models of immune-resistant lung carcinoma. This noninvasive and repeatable strategy represents a promising step forward in precision oncology and targeted cancer therapy.

Cluster of differentiation 44 (CD44), a versatile transmembrane glycoprotein, plays a crucial role in the progression, metastasis, and therapeutic resistance of colorectal cancer (CRC). This review clarifies CD44's essential function in CRC via connections with the extracellular matrix (ECM), particularly hyaluronic acid (HA), and important signaling pathways, such as Ras/mitogen-activated protein kinase/extracellular signal-regulated kinase and phosphoinositide 3-kinase/protein kinase B (PI3K/Akt). The overexpression of CD44, especially its variant isoforms (CD44v), is associated with aggressive tumor characteristics, increased cancer stem cell (CSC) traits, and unfavorable outcomes in CRC patients. CD44 enhances tumor cell attachment, movement, infiltration, and epithelial-mesenchymal transition, facilitating metastasis and resistance to chemotherapy. Its interactions with ECM elements and receptors, such as the epidermal growth factor receptor, enhance tumor growth and survival signaling. Therapeutic approaches aimed at CD44, such as monoclonal antibodies, small interfering RNAs, and nanoparticles targeting CD44 (e.g., CSA-SS-CXB@CPT, A@HAP), show encouraging antitumor effectiveness by interrupting CD44-HA interactions and the subsequent signaling pathways. Preclinical studies emphasize the benefits of pairing anti-CD44 therapies with PI3K/Akt or Wnt/β-catenin inhibitors to improve results. This review combines CD44's molecular mechanisms, isoform-specific functions, and CSC regulation in CRC, highlighting the potential as a biomarker and therapeutic target to enhance patient outcomes.